macro_germany_cpi_yearly

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds the source URL and return type (pandas.DataFrame), which is some context, but it does not disclose any behavioral traits such as the historical range covered, data frequency, or that it fetches from a live web endpoint.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely short, consisting of a title line, a URL, and a return-type docstring. It is efficient and front-loaded, with no wasted words. However, it reads more like a mechanical docstring than a thoughtfully written description, so it doesn't earn the top score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is a simple no-parameter retrieval, and the description states the source URL and return type, which is sufficient for a basic invocation. But it lacks information about the data's time span, update frequency, or any caveats, and there is no output schema to fill those gaps. It is minimally complete but leaves open questions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema is empty with 100% coverage. The description adds no parameter details, but none are needed. Per the baseline for 0-parameter tools, this scores 4 because the schema fully documents the absence of parameters and the description does not need to compensate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly identifies the resource: Germany's Consumer Price Index yearly rate final value from Eastmoney's data center. The title and URL provide specific context, but there is no explicit verb like 'retrieve' or 'get'; the purpose is implied by the name and title rather than stated directly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus alternative macro data tools, such as macro_germany_cpi_monthly or macro_germany_gdp. The description does not mention exclusions, prerequisites, or comparison to sibling tools, so the agent must infer usage purely from the name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.